Suppression of autophagic genes sensitizes CUG2-overexpressing A549 human lung cancer cells to oncolytic vesicular stomatitis virus-induced apoptosis
Bibliographic record
Abstract
We showed in our previous study that cancer upregulated gene (CUG) 2, a novel oncogene, confers resistance to infection of oncolytic vesicular stomatitis virus (VSV) by activating Stat1-mediated signal transduction. Since many studies have reported that autophagy is involved in virus replication, we investigated whether autophagy also plays a role in the antiviral activity in A549 cells overexpressing CUG2 (A549-CUG2). We suppressed Atg5 or Beclin 1 expression using siRNA and examined its effect on the susceptibility of cells to infection by oncolytic VSV. We found that A549-CUG2 cells treated with Atg5 or Beclin 1 siRNA became susceptible to VSV infection, whereas A549-CUG2 cells treated with control siRNA were resistant. This result suggests that autophagy is involved in the antiviral response of A549-CUG2 cells. Further investigation revealed that autophagy impairment enhanced the generation of reactive oxygen species (ROS), which resulted in inactivation of S6 kinase. Under these conditions, the levels of ISG15 transcript and protein decreased, which conferred on A549-CUG2 cell susceptibility to VSV infection. Finally, we found that overloading of H₂O₂ sensitized control A549-CUG2 cells to VSV-induced apoptosis. Taken together, these results indicate that autophagy impairment induces excessive ROS formation, which decreases S6 kinase activity and ISG15 expression, ultimately rendering the A549-CUG2 cells susceptible to VSV infection. We propose that autophagy impairment is a potential strategy for successful VSV virotherapy of CUG2-overexpressing tumors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".